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merged 2 commits into from
Oct 20, 2023
Merged

Fix loading Hub datasets with CSV metadata file #6316

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fc24544
Test load dataset with CSV metadata from Hub
albertvillanova Oct 19, 2023
1bdfba9
Pass metadata_ext to FolderBasedBuilder._read_metadata
albertvillanova Oct 19, 2023
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31 changes: 17 additions & 14 deletions src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -164,15 +164,15 @@ def analyze(files_or_archives, downloaded_files_or_dirs, split):

# Check that all metadata files share the same format
metadata_ext = {
os.path.splitext(downloaded_metadata_file)[1][1:]
for _, downloaded_metadata_file in itertools.chain.from_iterable(metadata_files.values())
os.path.splitext(original_metadata_file)[-1]
for original_metadata_file, _ in itertools.chain.from_iterable(metadata_files.values())
}
if len(metadata_ext) > 1:
raise ValueError(f"Found metadata files with different extensions: {list(metadata_ext)}")
metadata_ext = metadata_ext.pop()

for _, downloaded_metadata_file in itertools.chain.from_iterable(metadata_files.values()):
pa_metadata_table = self._read_metadata(downloaded_metadata_file)
pa_metadata_table = self._read_metadata(downloaded_metadata_file, metadata_ext=metadata_ext)
features_per_metadata_file.append(
(downloaded_metadata_file, datasets.Features.from_arrow_schema(pa_metadata_table.schema))
)
Expand Down Expand Up @@ -236,9 +236,8 @@ def _split_files_and_archives(self, data_files):
archives.append(data_file)
return files, archives

def _read_metadata(self, metadata_file):
metadata_file_ext = os.path.splitext(metadata_file)[1][1:]
if metadata_file_ext == "csv":
def _read_metadata(self, metadata_file, metadata_ext: str = ""):
if metadata_ext == ".csv":
# Use `pd.read_csv` (although slower) instead of `pyarrow.csv.read_csv` for reading CSV files for consistency with the CSV packaged module
return pa.Table.from_pandas(pd.read_csv(metadata_file))
else:
Expand All @@ -255,10 +254,10 @@ def _generate_examples(self, files, metadata_files, split_name, add_metadata, ad
metadata_dict = None
downloaded_metadata_file = None

metadata_ext = ""
if split_metadata_files:
metadata_ext = {
os.path.splitext(downloaded_metadata_file)[1][1:]
for _, downloaded_metadata_file in split_metadata_files
os.path.splitext(original_metadata_file)[-1] for original_metadata_file, _ in split_metadata_files
}
metadata_ext = metadata_ext.pop()

Expand Down Expand Up @@ -290,7 +289,9 @@ def _generate_examples(self, files, metadata_files, split_name, add_metadata, ad
_, metadata_file, downloaded_metadata_file = min(
metadata_file_candidates, key=lambda x: count_path_segments(x[0])
)
pa_metadata_table = self._read_metadata(downloaded_metadata_file)
pa_metadata_table = self._read_metadata(
downloaded_metadata_file, metadata_ext=metadata_ext
)
pa_file_name_array = pa_metadata_table["file_name"]
pa_metadata_table = pa_metadata_table.drop(["file_name"])
metadata_dir = os.path.dirname(metadata_file)
Expand All @@ -302,7 +303,7 @@ def _generate_examples(self, files, metadata_files, split_name, add_metadata, ad
}
else:
raise ValueError(
f"One or several metadata.{metadata_ext} were found, but not in the same directory or in a parent directory of {downloaded_file_or_dir}."
f"One or several metadata{metadata_ext} were found, but not in the same directory or in a parent directory of {downloaded_file_or_dir}."
)
if metadata_dir is not None and downloaded_metadata_file is not None:
file_relpath = os.path.relpath(original_file, metadata_dir)
Expand All @@ -314,7 +315,7 @@ def _generate_examples(self, files, metadata_files, split_name, add_metadata, ad
sample_metadata = metadata_dict[file_relpath]
else:
raise ValueError(
f"One or several metadata.{metadata_ext} were found, but not in the same directory or in a parent directory of {downloaded_file_or_dir}."
f"One or several metadata{metadata_ext} were found, but not in the same directory or in a parent directory of {downloaded_file_or_dir}."
)
else:
sample_metadata = {}
Expand Down Expand Up @@ -356,7 +357,9 @@ def _generate_examples(self, files, metadata_files, split_name, add_metadata, ad
_, metadata_file, downloaded_metadata_file = min(
metadata_file_candidates, key=lambda x: count_path_segments(x[0])
)
pa_metadata_table = self._read_metadata(downloaded_metadata_file)
pa_metadata_table = self._read_metadata(
downloaded_metadata_file, metadata_ext=metadata_ext
)
pa_file_name_array = pa_metadata_table["file_name"]
pa_metadata_table = pa_metadata_table.drop(["file_name"])
metadata_dir = os.path.dirname(downloaded_metadata_file)
Expand All @@ -368,7 +371,7 @@ def _generate_examples(self, files, metadata_files, split_name, add_metadata, ad
}
else:
raise ValueError(
f"One or several metadata.{metadata_ext} were found, but not in the same directory or in a parent directory of {downloaded_dir_file}."
f"One or several metadata{metadata_ext} were found, but not in the same directory or in a parent directory of {downloaded_dir_file}."
)
if metadata_dir is not None and downloaded_metadata_file is not None:
downloaded_dir_file_relpath = os.path.relpath(downloaded_dir_file, metadata_dir)
Expand All @@ -380,7 +383,7 @@ def _generate_examples(self, files, metadata_files, split_name, add_metadata, ad
sample_metadata = metadata_dict[downloaded_dir_file_relpath]
else:
raise ValueError(
f"One or several metadata.{metadata_ext} were found, but not in the same directory or in a parent directory of {downloaded_dir_file}."
f"One or several metadata{metadata_ext} were found, but not in the same directory or in a parent directory of {downloaded_dir_file}."
)
else:
sample_metadata = {}
Expand Down
71 changes: 71 additions & 0 deletions tests/test_upstream_hub.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,9 @@
import fnmatch
import gc
import os
import shutil
import tempfile
import textwrap
import time
import unittest
from io import BytesIO
Expand All @@ -17,13 +19,18 @@
ClassLabel,
Dataset,
DatasetDict,
DownloadManager,
Features,
Image,
Value,
load_dataset,
load_dataset_builder,
)
from datasets.config import METADATA_CONFIGS_FIELD
from datasets.packaged_modules.folder_based_builder.folder_based_builder import (
FolderBasedBuilder,
FolderBasedBuilderConfig,
)
from datasets.utils.file_utils import cached_path
from datasets.utils.hub import hf_hub_url
from tests.fixtures.hub import CI_HUB_ENDPOINT, CI_HUB_USER, CI_HUB_USER_TOKEN
Expand Down Expand Up @@ -813,3 +820,67 @@ def test_push_dataset_dict_to_hub_with_config_no_metadata_configs(self, temporar
ds_another_config_builder.config.data_files["random"][0],
"*/another_config/random-00000-of-00001.parquet",
)


class DummyFolderBasedBuilder(FolderBasedBuilder):
BASE_FEATURE = dict
BASE_COLUMN_NAME = "base"
BUILDER_CONFIG_CLASS = FolderBasedBuilderConfig
EXTENSIONS = [".txt"]
# CLASSIFICATION_TASK = TextClassification(text_column="base", label_column="label")


@pytest.fixture(params=[".jsonl", ".csv"])
def text_file_with_metadata(request, tmp_path, text_file):
metadata_filename_extension = request.param
data_dir = tmp_path / "data_dir"
data_dir.mkdir()
text_file_path = data_dir / "file.txt"
shutil.copyfile(text_file, text_file_path)
metadata_file_path = data_dir / f"metadata{metadata_filename_extension}"
metadata = textwrap.dedent(
"""\
{"file_name": "file.txt", "additional_feature": "Dummy file"}
"""
if metadata_filename_extension == ".jsonl"
else """\
file_name,additional_feature
file.txt,Dummy file
"""
)
with open(metadata_file_path, "w", encoding="utf-8") as f:
f.write(metadata)
return text_file_path, metadata_file_path


@for_all_test_methods(xfail_if_500_502_http_error)
@pytest.mark.usefixtures("ci_hub_config", "ci_hfh_hf_hub_url")
class TestLoadFromHub:
_api = HfApi(endpoint=CI_HUB_ENDPOINT)
_token = CI_HUB_USER_TOKEN

def test_load_dataset_with_metadata_file(self, temporary_repo, text_file_with_metadata, tmp_path):
text_file_path, metadata_file_path = text_file_with_metadata
data_dir_path = text_file_path.parent
cache_dir_path = tmp_path / ".cache"
cache_dir_path.mkdir()
with temporary_repo() as repo_id:
self._api.create_repo(repo_id, token=self._token, repo_type="dataset")
self._api.upload_folder(
folder_path=str(data_dir_path),
repo_id=repo_id,
repo_type="dataset",
token=self._token,
)
data_files = [
f"hf://datasets/{repo_id}/{text_file_path.name}",
f"hf://datasets/{repo_id}/{metadata_file_path.name}",
]
builder = DummyFolderBasedBuilder(
dataset_name=repo_id.split("/")[-1], data_files=data_files, cache_dir=str(cache_dir_path)
)
download_manager = DownloadManager()
gen_kwargs = builder._split_generators(download_manager)[0].gen_kwargs
generator = builder._generate_examples(**gen_kwargs)
result = [example for _, example in generator]
assert len(result) == 1